Advanced import scenarios¶
Increasingly users of OMERO are needing to go beyond the traditional “upload via a GUI”-style import model to more powerful methods.
There is a set of requirements for getting data into OMERO that is common to many institutions. Some of the requirements may be mutually exclusive.
Users need to get data off microscopes quickly. This likely includes not waiting for import to complete. Users will often move data immediately, or even save remotely during acquisition.
Users would like direct access to the binary repository file-system to read original files for analysis.
Users would like to view and begin working with images as soon as possible after acquisition.
Below we explain which options are available to you, and why there is a trade-off between the above requirements.
The “OMERO binary repository” (or repo) is the directory belonging to the OMERO user where files are imported:
The ManagedRepository directory inside of the repo is where files go during import into OMERO. Each user receives a top-level directory inside of “ManagedRepository” which fills with timestamped directories as imports accrue.
Depending on the permissions of this directory, users may or may not be able to see their imported files. Managing the permissions is the responsibility of the system administrator.
In “normal import”, files are copied to the OMERO binary repo via the API and so can work remotely or locally. In “in-place import”, files are “linked” into place.
In-place import is a new, powerful feature - it is critical that you read and understand the documentation before you consider using it.
Manual import (GUI)¶
This is the standard workflow and the one currently used at the University of Dundee. Users dump data to a shared file-system from the acquisition system, and then use the OMERO.insight client from the lab to import.
Users can validate that import worked.
Failed imports can be repeated and/or reported to QA etc.
Users do not have to wait for import to be scheduled.
Import destination is known: Project/Dataset etc.
Imports can be slow due to the data transfer from file-system to OMERO via the client.
Users must remember to delete data from the shared file-system to avoid data duplication.
Users cannot access the OMERO binary repo directly and must download original data via clients for local analysis.
Manual import (CLI)¶
Another typical workflow is that rather than using the GUI, users perform the same procedure as under “Manual import” but with the command-line (CLI) importer.
With a CLI workflow, it may be easier for users to connect remotely to kick off an import and to leave it running in the background for a long period of time.
All the same disadvantages apply as under “Manual import (GUI)”.
Cronjob import (manual delete)¶
For importing via cron, users still dump their data to a shared file-system from the acquisition system. They must have permissions to write to “their” directory which is mapped to a user in OMERO.
A cronjob starts a CLI import, possibly at night. The cronjob could be given admin rights in OMERO to perform an “Import As” for a particular user.
If a normal import is used, the cronjob would have to manually delete imported files from their original location to avoid duplication.
Users cannot work with their data in OMERO until some time after acquisition.
Failed imports are logged within the managed repository but not yet notified. Logs would probably need to be accessed via a sysadmin/cli. The cronjob could capture stdout and stderr and check for failures.
DropBox import (manual delete)¶
Similar to the cronjob scenario, DropBox importing requires that users drop their data in “their” directory which has special permissions for writing. The DropBox service monitors those directories for modifications and imports the files on a first-come-first-serve basis.
Users should see their data in OMERO quickly.
There is a limitation on the rate of new files in monitored locations.
There is also a limitation on which file systems can be used. A networked file share cannot be monitored by DropBox.
Users must manually delete imported files from their DropBox directory to avoid duplication.
Failed imports are logged within the managed repository but not yet notified. Logs would probably need to be accessed via a sysadmin or through the CLI and searched by the user and file name.
DropBox import (automatic delete)¶
One option is to have files removed from DropBox automatically after a successful import. This is achieved by performing an “upload” import from the DropBox directory to the ManagedRepository then deleting the data from DropBox if and only if the import was successful. For failed imports, files will remain in the DropBox directories until someone manually deletes them.
For all successful imports, files will be automatically removed from the DropBox directories thus reducing duplication.
The following sections outline in-place based scenarios to help you judge if the functionality may be useful for you.
All in-place import scenarios provide non-copying benefit. Data that is too large to exist in multiple places, or which is accessed too frequently in its original form to be renamed, remains where it was originally acquired.
Like the DropBox import scenario above, all in-place imports require the user to have access to the user-based directories under the ManagedRepository. See limitations for more details.
Similarly, all the following scenarios carry the same burden of securing the data externally to OMERO. This is the primary difference between a normal import and an in-place import: backing up OMERO is no longer sufficient to prevent data loss. The original location must also be secured! This means that users must not move or alter data once imported.
In-place manual import (CLI)¶
The in-place version of a CLI manual import is quite similar to the normal CLI import, with the primary difference being that the data is not transferred from the shared file-system where the data is initially stored after acquisition, but instead is just “linked” into place.
Local filesystem in-place import is faster than traditional importing, due to the lack of a data transfer.
Requires proper security setup as explained above.
In-place Cronjob import¶
Assuming all the restrictions are met, the cronjob-based workflow above can carry out an in-place import by adding the in-place transfer flag. The advantages and disadvantages are as above.
In-place DropBox import (manual delete)¶
Just as with the in-place cronjob import, using in-place import for DropBox is as straight-forward as passing the in-place flag. The common advantages and disadvantages of in-place import apply.
In-place DropBox import (automatic delete)¶
An option that also exists in the in-place scenario is to have files removed from DropBox automatically after a successful import. This is achieved by first performing a “hardlink in-place import” from the DropBox directory to the ManagedRepository and then by deleting the data from DropBox if and only if the import was successful. For failed imports, files will remain in the DropBox directories until someone manually deletes them.
For all successful imports, files will be automatically removed from the DropBox directories.
This option is only available if the filesystem which DropBox watches is the same as the file system which the ManagedRepository lives on. This prevents the use of network file systems and similar remote shares.
Parallel import is a variant of manual CLI import for making large-scale imports considerably faster. It is experimental and may see extensive changes between patch versions. Use of this feature entails risk: if high thread counts are specified then the import client or OMERO server may function poorly. New uses of parallel import should be tested with a non-production server. Experience gained within OME and reported by users will help to make parallel import more friendly and safe.
omero import --parallel-fileset sets how many filesets are
imported at the same time.
omero import --parallel-upload sets
how many files are uploaded at the same time. File upload occurs early
in import and the fileset import threads share the same file upload
threads among them so it typically makes sense to set the file upload
thread count at least as high as the fileset import thread count. They
both default to a value of 1.
These options can provide clear benefits if set even at lower numbers like 4. Do not assume that higher is always better: more concurrent threads means higher overhead and may severely exhaust resources on the server and the client. Issues with parallel import include:
Import can fail when the same repository directory is being created to hold the files from different filesets. An effective workaround is to set the server’s Template path such that the
%thread%term precedes any subdirectories that may need to be created at import time.
Import can fail when the same import target is created to contain multiple filesets. An effective workaround is to create the targets in advance of starting the imports.
The server’s connections to the database may become saturated, making the server unresponsive. Set the
omero.db.poolsizeproperty higher than the number of filesets that will be imported across all users at any one time.